[1] 557
[38;5;246m# A tibble: 0 × 5[39m
[38;5;246m# Groups:   Year [0][39m
[38;5;246m# ℹ 5 variables: Year <dbl>, AMLawName <chr>, PPP1 <dbl>, PPP2 <dbl>,[39m
[38;5;246m#   total_income <dbl>[39m
[38;5;246m# A tibble: 1 × 2[39m
  Lobbyist        Lobbyist_id 
  [3m[38;5;246m<chr>[39m[23m           [3m[38;5;246m<chr>[39m[23m       
[38;5;250m1[39m Cohen, H Rodgin Y0000001648L
[38;5;246m# A tibble: 8 × 2[39m
  Lobbyist          Lobbyist_id 
  [3m[38;5;246m<chr>[39m[23m             [3m[38;5;246m<chr>[39m[23m       
[38;5;250m1[39m Ireland, Kathleen Y0000010400L
[38;5;250m2[39m Ireland, Kathy    Y0000052934L
[38;5;250m3[39m Ireland, Walter   Y0000025445L
[38;5;250m4[39m Ireland, Oliver I Y0000041124L
[38;5;250m5[39m Ireland, Andy     Y0000007730L
[38;5;250m6[39m Ireland, Evelyn   Y0000039505L
[38;5;250m7[39m Ireland, Jeanne C Y0000040237L
[38;5;250m8[39m Ireland, Patricia Y0000041627L
[38;5;246m# A tibble: 22 × 2[39m
   Lobbyist              Lobbyist_id 
   [3m[38;5;246m<chr>[39m[23m                 [3m[38;5;246m<chr>[39m[23m       
[38;5;250m 1[39m Bush, Antoinette Cook Y0000041172L
[38;5;250m 2[39m Bushman, Michael R    Y0000008199L
[38;5;250m 3[39m Bush, Milton M        Y0000024257L
[38;5;250m 4[39m Bushway, Christine    Y0000043384L
[38;5;250m 5[39m Bushnell, David       Y0000041587L
[38;5;250m 6[39m Bushnell, Gary        Y0000030867L
[38;5;250m 7[39m Bushell, Gary         Y0000013046L
[38;5;250m 8[39m Bush, Barbara         Y0000009229L
[38;5;250m 9[39m Bushue, Sandra K      Y0000011633L
[38;5;250m10[39m Bush, Edwin F         Y0000037130L
[38;5;246m# ℹ 12 more rows[39m
[38;5;246m# A tibble: 1 × 2[39m
  Lobbyist       Lobbyist_id 
  [3m[38;5;246m<chr>[39m[23m          [3m[38;5;246m<chr>[39m[23m       
[38;5;250m1[39m Guynn, Randall Y0000038820L
[38;5;246m# A tibble: 1 × 2[39m
  Lobbyist  Lobbyist_id 
  [3m[38;5;246m<chr>[39m[23m     [3m[38;5;246m<chr>[39m[23m       
[38;5;250m1[39m Lee, Paul Y0000000213L
[38;5;246m# A tibble: 1 × 2[39m
  Lobbyist       Lobbyist_id 
  [3m[38;5;246m<chr>[39m[23m          [3m[38;5;246m<chr>[39m[23m       
[38;5;250m1[39m Walsh, Carolyn Y0000024109L
[38;5;246m# A tibble: 160 × 2[39m
   Lobbyist                 Lobbyist_id 
   [3m[38;5;246m<chr>[39m[23m                    [3m[38;5;246m<chr>[39m[23m       
[38;5;250m 1[39m Davis, Lynda             Y0000003239L
[38;5;250m 2[39m Davis, Richard H         Y0000040574L
[38;5;250m 3[39m Davis, Robert V          Y0000023839L
[38;5;250m 4[39m Davis, George A          Y0000006370L
[38;5;250m 5[39m Davis, Drew M            Y0000000884L
[38;5;250m 6[39m Davis, Bob               Y0000001715L
[38;5;250m 7[39m Henderson, Shannon Davis Y0000005805L
[38;5;250m 8[39m Davis, Jim               Y0000012620L
[38;5;250m 9[39m Davison, Robert          Y0000049699L
[38;5;250m10[39m Davis, Randall E         Y0000008406L
[38;5;246m# ℹ 150 more rows[39m
[38;5;246m# A tibble: 6 × 2[39m
   Year `sum(Total, na.rm = T)`
  [3m[38;5;246m<int>[39m[23m                   [3m[38;5;246m<int>[39m[23m
[38;5;250m1[39m  [4m2[24m016                95[4m7[24m[4m6[24m[4m0[24m898
[38;5;250m2[39m  [4m2[24m017                97[4m4[24m[4m2[24m[4m1[24m685
[38;5;250m3[39m  [4m2[24m018                99[4m4[24m[4m7[24m[4m3[24m071
[38;5;250m4[39m  [4m2[24m019               100[4m3[24m[4m2[24m[4m0[24m992
[38;5;250m5[39m  [4m2[24m020               103[4m2[24m[4m4[24m[4m1[24m218
[38;5;250m6[39m  [4m2[24m021                26[4m0[24m[4m1[24m[4m4[24m537
[38;5;246m# A tibble: 24 × 2[39m
    Year `sum(Amount)`
   [3m[38;5;246m<int>[39m[23m         [3m[38;5;246m<dbl>[39m[23m
[38;5;250m 1[39m  [4m1[24m998      31[4m9[24m[4m5[24m[4m4[24m883
[38;5;250m 2[39m  [4m1[24m999      35[4m5[24m[4m0[24m[4m2[24m641
[38;5;250m 3[39m  [4m2[24m000      44[4m0[24m[4m5[24m[4m4[24m562
[38;5;250m 4[39m  [4m2[24m001      38[4m8[24m[4m6[24m[4m5[24m903
[38;5;250m 5[39m  [4m2[24m002      42[4m6[24m[4m8[24m[4m5[24m858
[38;5;250m 6[39m  [4m2[24m003      49[4m3[24m[4m0[24m[4m5[24m601
[38;5;250m 7[39m  [4m2[24m004      55[4m2[24m[4m2[24m[4m3[24m610
[38;5;250m 8[39m  [4m2[24m005      59[4m6[24m[4m0[24m[4m2[24m321
[38;5;250m 9[39m  [4m2[24m006      64[4m0[24m[4m2[24m[4m0[24m809
[38;5;250m10[39m  [4m2[24m007      89[4m5[24m[4m1[24m[4m4[24m741
[38;5;246m# ℹ 14 more rows[39m
[38;5;246m# Source:   SQL [?? x 6][39m
[38;5;246m# Database: sqlite 3.39.3 [/Users/brianlibgober/Dropbox/Collaborations/Lawyers As Lobbyists/ReplicationFolder/Data/opensecretslobbying_2021-06-09.sqlite][39m
   Catcode Catname                        Catorder Industry Sector `Sector Long`
   [3m[38;5;246m<chr>[39m[23m   [3m[38;5;246m<chr>[39m[23m                          [3m[38;5;246m<chr>[39m[23m    [3m[38;5;246m<chr>[39m[23m    [3m[38;5;246m<chr>[39m[23m  [3m[38;5;246m<chr>[39m[23m        
[38;5;250m 1[39m F0000   Finance, Insurance & Real Est… F13      Misc Fi… Finan… Finance, Ins…
[38;5;250m 2[39m F1000   Banks & lending institutions   F03      Commerc… Finan… Finance, Ins…
[38;5;250m 3[39m F1100   Commercial banks & bank holdi… F03      Commerc… Finan… Finance, Ins…
[38;5;250m 4[39m F1200   Savings banks & Savings and L… F04      Savings… Finan… Finance, Ins…
[38;5;250m 5[39m F1300   Credit unions                  F05      Credit … Finan… Finance, Ins…
[38;5;250m 6[39m F1400   Credit agencies & finance com… F06      Finance… Finan… Finance, Ins…
[38;5;250m 7[39m F1410   Student loan companies         F06      Finance… Finan… Finance, Ins…
[38;5;250m 8[39m F1420   Payday lenders                 F06      Finance… Finan… Finance, Ins…
[38;5;250m 9[39m F2000   Securities, commodities & inv… F07      Securit… Finan… Finance, Ins…
[38;5;250m10[39m F2100   Security brokers & investment… F07      Securit… Finan… Finance, Ins…
[38;5;246m# ℹ more rows[39m
[1] 5435
[1] 4371
[1] 1661
[38;5;246m# A tibble: 2 × 2[39m
[38;5;246m# Groups:   has_credential [2][39m
  has_credential     n
  [3m[38;5;246m<lgl>[39m[23m          [3m[38;5;246m<int>[39m[23m
[38;5;250m1[39m TRUE             650
[38;5;250m2[39m [31mNA[39m              [4m3[24m866
[38;5;246m# A tibble: 2 × 2[39m
[38;5;246m# Groups:   has_law_credential [2][39m
  has_law_credential     n
  [3m[38;5;246m<lgl>[39m[23m              [3m[38;5;246m<int>[39m[23m
[38;5;250m1[39m FALSE                400
[38;5;250m2[39m TRUE                 250
[38;5;246m# A tibble: 3 × 2[39m
[38;5;246m# Groups:   Government [3][39m
  Government     n
  [3m[38;5;246m<lgl>[39m[23m      [3m[38;5;246m<int>[39m[23m
[38;5;250m1[39m FALSE       [4m6[24m155
[38;5;250m2[39m TRUE        [4m1[24m470
[38;5;250m3[39m [31mNA[39m             1
[38;5;246m# A tibble: 2 × 2[39m
[38;5;246m# Groups:   met.with.fed [2][39m
  met.with.fed     n
  [3m[38;5;246m<lgl>[39m[23m        [3m[38;5;246m<int>[39m[23m
[38;5;250m1[39m FALSE        [4m4[24m[4m9[24m748
[38;5;250m2[39m TRUE           953
[1] 319
[1] 235
[1] 15
[1] "DONE!"
